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    Artificial Intelligence Masterclass + ChatGPT Prize

    BY
    Udemy

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    Mode

    Online

    Fees

    ₹ 599 3699

    Quick Facts

    particular details
    Medium of instructions English
    Mode of learning Self study
    Mode of Delivery Video and Text Based

    Course and certificate fees

    Fees information
    ₹ 599  ₹3,699
    certificate availability

    Yes

    certificate providing authority

    Udemy

    The syllabus

    Introduction

    • Updates on Udemy Reviews
    • Introduction + Course Structure + Demo
    • BONUS: Learning Paths
    • Your Three Best Resources
    • Download the Resources here
    • Meet your instructors!

    Step 1 - Artificial Neural Network

    • Welcome to Step 1 - Artificial Neural Network
    • Plan of Attack
    • The Neuron
    • The Activation Function
    • How do Neural Networks work?
    • How do Neural Networks learn?
    • Gradient Descent
    • Stochastic Gradient Descent
    • Backpropagation

    Step 2 - Convolutional Neural Network

    • Welcome to Step 2 - Convolutional Neural Network
    • Plan of Attack
    • What are Convolutional Neural Networks?
    • Step 1 - The Convolution Operation
    • Step 1 Bis - The ReLU Layer
    • Step 2 - Pooling
    • Step 3 - Flattening
    • Step 4 - Full Connection
    • Summary
    • Softmax & Cross-Entropy

    Step 3 - AutoEncoder

    • Welcome to Step 3 - AutoEncoder
    • Plan of Attack
    • What are AutoEncoders?
    • A Note on Biases
    • Training an AutoEncoder
    • Overcomplete Hidden Layers
    • Sparse AutoEncoders
    • Denoising AutoEncoders
    • Contractive AutoEncoders
    • Stacked AutoEncoders
    • Deep AutoEncoders

    Step 4 - Variational AutoEncoder

    • Welcome to Step 4 - Variational AutoEncoder
    • Introduction to the VAE
    • Variational AutoEncoders
    • Reparameterization Trick

    Step 5 - Implementing the CNN-VAE

    • Welcome to Step 5 - Implementing the CNN-VAE
    • Introduction to Step 5
    • Initializing all the parameters and variables of the CNN-VAE class
    • Building the Encoder part of the VAE
    • Building the "V" part of the VAE
    • Building the Decoder part of the VAE
    • Implementing the Training operations
    • Full Code Section
    • The Keras Implementation

    Step 6 - Recurrent Neural Network

    • Welcome to Step 6 - Recurrent Neural Network
    • Plan of Attack
    • What are Recurrent Neural Networks?
    • The Vanishing Gradient Problem
    • LSTMs
    • LSTM Practical Intuition
    • LSTM Variations

    Step 7 - Mixture Density Network

    • Welcome to Step 7 - Mixture Density Network
    • Introduction to the MDN-RNN
    • Mixture Density Networks
    • VAE + MDN-RNN Visualization

    Step 8 - Implementing the MDN-RNN

    • Welcome to Step 8 - Implementing the MDN-RNN
    • Initializing all the parameters and variables of the MDN-RNN class
    • Building the RNN - Gathering the parameters
    • Building the RNN - Creating an LSTM cell with Dropout
    • Building the RNN - Setting up the Input, Target, and Output of the RNN
    • Building the RNN - Getting the Deterministic Output of the RNN
    • Building the MDN - Getting the Input, Hidden Layer and Output of the MDN
    • Building the MDN - Getting the MDN parameters
    • Implementing the Training operations (Part 1)
    • Implementing the Training operations (Part 2)
    • Full Code Section
    • The Keras Implementation

    Step 9 - Reinforcement Learning

    • Welcome to Step 9 - Reinforcement Learning
    • What is Reinforcement Learning?
    • A Pseudo Implementation of Reinforcement Learning for the Full World Model
    • Full Code Section

    Step 10 - Deep NeuroEvolution

    • Welcome to Step 10 - Deep NeuroEvolution
    • Deep NeuroEvolution
    • Evolution Strategies
    • Genetic Algorithms
    • Covariance-Matrix Adaptation Evolution Strategy (CMA-ES)
    • Parameter-Exploring Policy Gradients (PEPG)
    • OpenAI Evolution Strategy

    The Final Run

    • The Whole Implementation
    • Download the whole AI Masterclass folder here
    • Installing the required packages
    • The Final Race: Human Intelligence vs. Artificial Intelligence
    • THANK YOU bonus video

    Bonus Lectures

    • ***YOUR SPECIAL BONUS***

    Instructors

    Mr Hadelin de Ponteves

    Mr Hadelin de Ponteves
    Co-founder
    Udemy

    Mr Kirill Eremenko

    Mr Kirill Eremenko
    Data Scientist
    Udemy

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